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1
Multimodal Lip-Reading for Tracheostomy Patients in the Greek Language
In: Computers; Volume 11; Issue 3; Pages: 34 (2022)
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2
Semantic Fusion for Natural Multimodal Interfaces using Concurrent Augmented Transition Networks
In: Multimodal Technologies and Interaction ; Volume 2 ; Issue 4 (2018)
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3
Mining a Multimodal Corpus of Doctor's Training for Virtual Patient's Feedbacks
In: 19th International Conference on Multimodal Interaction (ICMI) ; https://hal.archives-ouvertes.fr/hal-01654812 ; 19th International Conference on Multimodal Interaction (ICMI), Nov 2017, Glasgow, United Kingdom. ⟨10.1145/3136755.3136816⟩ (2017)
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4
ENHANCING EXPRESSIVITY OF DOCUMENT-CENTERED COLLABORATION WITH MULTIMODAL ANNOTATIONS
Yoon, Dongwook. - 2017
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5
ДВУЯЗЫЧНАЯ МНОГОМОДАЛЬНАЯ СИСТЕМА ДЛЯ АУДИОВИЗУАЛЬНОГО СИНТЕЗА РЕЧИ И ЖЕСТОВОГО ЯЗЫКА ПО ТЕКСТУ
КАРПОВ АЛЕКСЕЙ АНАТОЛЬЕВИЧ; ЖЕЛЕЗНЫ МИЛОШ. - : Федеральное государственное автономное образовательное учреждение высшего образования «Санкт-Петербургский национальный исследовательский университет информационных технологий, механики и оптики», 2014
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6
Robust Multimodal Cognitive Load Measurement
In: DTIC (2014)
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7
Robust Multimodal Cognitive Load Measurement (RMCLM)
In: DTIC (2013)
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8
Interactive multi-modal question-answering
Bosch, Antal van den; Bouma, Gosse. - Berlin : Springer, 2011
MPI für Psycholinguistik
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9
Effective and Spurious Ambiguities due to some Co-verbal Gestures in multimodal dialogue
In: Eighth International Gesture Workshop (GW 2009) ; https://halshs.archives-ouvertes.fr/halshs-00436903 ; Eighth International Gesture Workshop (GW 2009), Feb 2009, Bielefeld, Germany (2009)
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10
Between linguistic attention and gaze fixations in multimodal conversational interfaces
In: http://web.cse.msu.edu/~fangrui/Papers/ICMI09.pdf (2009)
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11
Ishizuka M.: Automatic generation of gaze and gestures for dialogues between embodied conversational agents
In: http://research.nii.ac.jp/%7Eprendinger/papers/werner-helmut-IJSC-08.pdf (2008)
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12
Multi modal gesture identification for HCI using surface EMG
Naik, Ganesh R. (R19010); Kumar, Dinesh K.; Arjunan, Sridhar P.. - : U.S., Association for Computing Machinery, 2008
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13
Timing of visual and spoken input in robot instructions
In: http://www.swrtec.de/swrtec/research/publications/WolfBugmannsubmissionv3.pdf (2006)
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14
Using redundant speech and handwriting for learning new vocabulary and understanding abbreviations
In: https://pal.sri.com/CALOfiles/cstore/PAL-publications/calo/2006/p347-kaiser.pdf (2006)
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15
Collaborative multimodal photo annotation over digital paper
In: http://pdf.aminer.org/000/334/219/collaborative_multimodal_photo_annotation_over_digital_paper.pdf (2006)
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16
Effective error recovery strategies for multimodal form-filling applications
In: http://lands.let.kun.nl/literature/sturm.2005.1.pdf (2005)
Abstract: The goal of the research described in this article is to determine in what way speech recognition errors can be handled best in a multimodal form-filling interface. Besides two well-known error correction mechanisms (re-speaking the value and choosing the correct value from a list of alternatives), the interface o#ers a novel correction mechanism in which the user selects the first letter of the target word from a soft-keyboard, after which the utterance is recognized once again, with a limited language model and lexicon. The multimodal interface that was used is a web-based form-filling GUI, extended with a speech overlay, which allows for pen and speech input. The e#ectiveness and e#- ciency of the error correction mechanisms, the error correction strategies that are applied by the users and the effects on user satisfaction were studied in an evaluation in which the interface was tested in two conditions: in one condition (LIST), the interface provides only re-speaking and the alternatives list as error correction facilities. In the other condition (LETTER), the interface provides the soft-keyboard technique as an additional error correction facility. The study shows that error correction was more effective in the LETTER condition than in the LIST condition. The Keyboard correction facility enables the users to solve errors that could not be solved using the Re-speak method or by choosing from a list of alternatives. In spite of its low effectiveness, subjects initially attempted to use Re-speaking for error correction in both interfaces. However, we also found that subjects rapidly learned to choose the most effective option (Keyboard) immediately as they gain experience. The user satisfaction turned out to be higher for the LETTER interface than for the LIST interface: .
Keyword: Error correction; Multimodal interfaces; Speech recognition
URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.62.406
http://lands.let.kun.nl/literature/sturm.2005.1.pdf
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17
Distributed pointing for multimodal collaboration over sketched diagrams
In: http://calosystem.com/publications/downloads/kaiser/distpointingmultimodal-kaiser.pdf (2005)
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18
Distributed Pointing for Multimodal Collaboration Over Sketched Diagrams. ICMI
In: http://www.barthelmess.net/Publications/ICMI/p10-barthelmess.pdf (2005)
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19
Linguistic theories in efficient multimodal reference resolution: An empirical investigation
In: http://www.soc.northwestern.edu/justine/discourse07/week2/Chai_LinguisticTheories.pdf (2005)
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20
Multimodal new vocabulary recognition through speech and handwriting in a whiteboard scheduling application
In: http://www.cse.ogi.edu/CHCC/Publications/Multimodal_New_Vocabulary_Recognition_through_Speech_and_Handwriting_in_a_Whiteboard_Scheduling_Application.pdf (2005)
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